I help organizations transform revenue, pipeline, customer, and commercial data into actionable business insights that improve growth, forecasting accuracy, sales performance, and executive decision-making.
With 10+ years of experience across commercial operations, sales, trade marketing, logistics, and business intelligence, I combine deep business expertise with modern analytics capabilities to solve real-world revenue challenges.
📈 Revenue Analytics
🎯 Revenue Operations
💰 Commercial Intelligence
📊 Sales & Funnel Analytics
👥 Customer Analytics
🔮 Revenue Forecasting
📋 Executive Reporting
⚙️ Data Quality & Governance
An end-to-end Revenue Intelligence solution designed to improve visibility into pipeline performance, sales effectiveness, customer value, and revenue growth.
📊 2ドル.0B Pipeline Analyzed
💰 342ドル.8M Revenue Tracked
🎯 100K Leads Evaluated
👥 10K Customer Records
• Revenue Analytics
• Funnel Analytics
• Customer Intelligence
• Sales Performance Analytics
• Executive KPI Reporting
🔗 Repository: Revenue Operations Intelligence Platform
An end-to-end analytics solution designed to evaluate marketing effectiveness, forecast revenue impact, and optimize budget allocation decisions.
✅ Marketing Mix Modeling
✅ Revenue Forecasting
✅ Budget Optimization
✅ Scenario Analysis
✅ Channel Performance Evaluation
✅ Executive Marketing Dashboards
- Quantified channel-level marketing effectiveness
- Simulated budget reallocation scenarios
- Delivered revenue optimization recommendations
- Supported data-driven marketing investment decisions
🔗 Repository: Marketing Mix Modeling & Revenue Optimization
Identifying Conversion Bottlenecks, Retention Decay, and High-ROI Channels
🚀 End-to-end analytics project combining SQL, Python, and Power BI to diagnose where growth breaks across the marketing funnel and how to fix it.
- 🚨 Largest drop-off at SQL → Customer (~67%)
- 📉 Conversions heavily front-loaded (0–30 days)
- 🔁 No delayed conversion or lifecycle recovery
- 💸 LinkedIn shows high CAC with low conversion
This system enables:
- 🎯 Identification of conversion bottlenecks
- 📉 Reduction of funnel drop-off
- 💰 Optimization of marketing spend
- 📊 Better allocation across channels
- 🔁 Integration of acquisition + conversion + retention
🔗 Repository: Cohort-Based Marketing Funnel Analysis)
An automated data quality framework designed to identify anomalies, duplicates, inconsistencies, and reporting issues across operational datasets.
✅ Data Validation
✅ Data Quality Monitoring
✅ Reporting Governance
✅ Process Automation
✅ KPI Monitoring
This system demonstrates how raw administrative data can be transformed into a governed analytical asset that supports:
- ✅ Improved revenue forecasting accuracy
- ✅ Better policy decision-making
- ✅ Early detection of data degradation
- ✅ Increased trust in reporting systems
- ✅ Reduced manual data validation effort
📌 Key Insight: Data quality issues are not reporting errors — they are decision risks.
🔗 Repository: Data Quality Monitoring & Governance System
Power BI SQL Python DAX Power Query
• Revenue Analytics
• Revenue Operations
• Commercial Intelligence
• Revenue Forecasting
• Pipeline Analytics
• Customer Analytics
• Sales Analytics
• Business Intelligence
✔ 10+ years of commercial, sales, operations, and analytics experience
✔ Built enterprise-scale Revenue Operations, Marketing Analytics, and Business Intelligence solutions
✔ Experienced in forecasting, KPI governance, executive reporting, and performance optimization
✔ Passionate about helping organizations improve revenue performance through data-driven decision-making
💼 LinkedIn www.linkedin.com/in/abodunrin-oketade
📂 GitHub Portfolio https://github.com/Richie-Rokka
📧 Email aoketade@gmail.com
"Data becomes valuable when it drives better decisions."